HalfCheetah Experiments. As in [1]}, we sample a target velocity for the agent from \(U[0, 3]\) , which is passed in as part of the state to the expert but hidden from the learner. We train an expert for this task via Soft Actor Critic (SAC) [2]} – we refer interested readers to our code for precise hyperparameters. The reward function we train the expert and evaluate learner policies with is
\(1 -|\dot{x_t} - c| - 0.05 ||u_t||_2^2,\) 
